Regression techniques for Portfolio Optimisation using MOSEK
Portfolio Management
2013-10-16 v1 Optimization and Control
Abstract
Regression is widely used by practioners across many disciplines. We reformulate the underlying optimisation problem as a second-order conic program providing the flexibility often needed in applications. Using examples from portfolio management and quantitative trading we solve regression problems with and without constraints. Several Python code fragments are given. The code and data are available online at http://www.github.com/tschm/MosekRegression.
Keywords
Cite
@article{arxiv.1310.3397,
title = {Regression techniques for Portfolio Optimisation using MOSEK},
author = {Thomas Schmelzer and Raphael Hauser and Erling Andersen and Joachim Dahl},
journal= {arXiv preprint arXiv:1310.3397},
year = {2013}
}